The present invention generally relates to development and operations data, and more specifically, to root cause analysis for correlated development and operations data.
Customers, typically, want to identify the root-cause and risk factors associated with performance issues. However, some transactions are too complex to review. With thousands of artifacts and very complex call graphs, review can be time-consuming and labor-intensive, especially when analyzing graphs and metrics manually. Also, there are no correlations of different levels of data to help a customer find and understand a root-cause. While transaction composition and static analysis data are available, the amount of data can be very large and present difficulties when users drill down to whole application and application parts levels to try and find the problem themselves.